Weeks, not months: how Chiesi rebuilt the foundation for its workforce transformation

Mathieu De Baets
September 24, 2026
3 min read
Contents

Chiesi redesigned its job architecture from the ground up with TechWolf's Job Architecture Redesign Agent, new job descriptions included, and put it live in SAP SuccessFactors in a matter of weeks.

Boards are investing heavily in AI and asking where the return is. Much of the answer sits inside the workforce. Work is being redesigned in every function, but until that new work is captured in roles, levels and skills, it has nowhere to land. Pilots stay pilots.

The structure it should land in is the job architecture. In most organisations, that architecture is years out of date.

The starting point

Chiesi, the global pharmaceutical group, had job titles and a grading structure. What it lacked was a job architecture detailed enough to build on.

We were missing a real connection between the work that each person was doing and how this was captured in our Job Architecture."

— Marco Camin, Head of People Tech & Insights at Chiesi

Without actually capturing the granular work happening within the organization, and without consistent job descriptions, skills could not be reliably attached to roles. That put the value of Chiesi's investment in skills intelligence, and in SAP SuccessFactors Talent Intelligence Hub, on hold. The foundation was the gate.

Redesigning from the ground up

Instead of fitting Chiesi into a generic template, the work started from what already existed. Every position title linked to a job went into the Redesign Agent. The Agent analysed the work behind those titles, grouped it into job roles representing distinct skill profiles. Seniority was then applied using Chiesi's levelling framework from WTW.

Chiesi's team stayed in control throughout. The Agent drafted, the team reviewed and decided.

The result was a structurally redesigned job architecture, a new level-aware job description for every job in it, and job titles and employees remapped to the new roles.

Our mutual partner, TalenTeam, configured SAP SuccessFactors alongside the redesign and brought the new architecture live in SAP Job Profile Builder.

Weeks, not months

We completed the redesign in a matter of weeks, including the remapping of job titles and employees and uploading it into SAP Job Profile Builder. Without the Agent it would have been far more complex, and it would have taken months."

— Letizia Gasparri, VP Global Talent at Chiesi

Speed is only half of the story. Because the architecture was built from the work people actually do, business stakeholders could recognise their own roles in it. That made validation far easier: instead of debating an abstract model, leaders were checking whether the structure reflected their teams, and it did.

What it unlocks

Chiesi now has a single source of truth for how roles, work and skills change with AI.

It also changes the shelf life of the architecture. Job architectures typically go untouched for years while the organisation reorganises around them. Because this one was built with the Job Architecture Redesign Agent, it can be maintained as roles change, instead of waiting for the next big project.

That is the difference between redesigning work on paper and making it real.

See the Job Architecture Redesign Agent live at SAP Connect, Las Vegas, 5 to 7 October.

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Using AI while interviewing at Techwolf

At TechWolf, we see generative AI as part of the modern toolkit — and we expect candidates to treat it that way too. We love it when people use AI to take their thinking to the next level, rather than to replace it.You are welcome to use tools like ChatGPT, Claude, or others during our interview process, especially in take-home assignments or technical exercises. We encourage you to bring your full toolkit — and that includes AI — as long as it reflects your own thinking, decisions and creativity.We don’t see AI as replacing your skills. Instead, we’re interested in how you use it: to brainstorm ideas, speed up iteration, validate your thinking, or unlock new ways of approaching a challenge. Great candidates show judgment in when to rely on AI, how to adapt its output, and where to go beyond it.

What we’re looking for:

Our interviews are designed to understand how you think, solve problems, and express ideas. Using AI in a way that amplifies those things — not masks them — is encouraged.

What to avoid:

We ask that you don’t submit AI-generated work without review, or present answers that you can’t fully explain. We’re not testing the model — we’re getting to know you, your skills, and your potential. If there are cases where we don’t want you to use AI for something, we’ll tell you ahead of the interview being booked.In short: use AI as you would on the job — as a smart assistant, not a stand-in.

Example: Programming with AI

In a coding challenge, you’re welcome to use generative AI to support your workflow — just like you might in a real development environment. For instance, you might use AI to quickly generate boilerplate code, look up syntax, or get a first-pass solution that you then adapt and debug collaboratively. What we’re interested in is your ability to reason through trade-offs, communicate clearly, think about complexity and iterate effectively — not whether you memorized the syntax perfectly. If using AI helps you stay in flow and focus on higher-level problem-solving, we consider that a strength. There could be some challenges where we won’t allow you to use AI - in that case we’ll tell you in advance, and will tell you why.